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RNA-seq: impact of RNA degradation on transcript quantification

Overview of attention for article published in BMC Biology, May 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)

Mentioned by

blogs
2 blogs
twitter
32 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
265 Dimensions

Readers on

mendeley
654 Mendeley
citeulike
1 CiteULike
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Title
RNA-seq: impact of RNA degradation on transcript quantification
Published in
BMC Biology, May 2014
DOI 10.1186/1741-7007-12-42
Pubmed ID
Authors

Irene Gallego Romero, Athma A Pai, Jenny Tung, Yoav Gilad

Abstract

The use of low quality RNA samples in whole-genome gene expression profiling remains controversial. It is unclear if transcript degradation in low quality RNA samples occurs uniformly, in which case the effects of degradation can be corrected via data normalization, or whether different transcripts are degraded at different rates, potentially biasing measurements of expression levels. This concern has rendered the use of low quality RNA samples in whole-genome expression profiling problematic. Yet, low quality samples (for example, samples collected in the course of fieldwork) are at times the sole means of addressing specific questions.

Twitter Demographics

The data shown below were collected from the profiles of 32 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 654 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 16 2%
United Kingdom 6 <1%
Spain 4 <1%
Germany 2 <1%
Brazil 2 <1%
Finland 1 <1%
Uruguay 1 <1%
Austria 1 <1%
Czechia 1 <1%
Other 7 1%
Unknown 613 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 186 28%
Researcher 147 22%
Student > Master 76 12%
Student > Bachelor 49 7%
Student > Doctoral Student 26 4%
Other 94 14%
Unknown 76 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 269 41%
Biochemistry, Genetics and Molecular Biology 148 23%
Medicine and Dentistry 31 5%
Neuroscience 21 3%
Computer Science 20 3%
Other 74 11%
Unknown 91 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 31. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 April 2018.
All research outputs
#540,556
of 13,583,549 outputs
Outputs from BMC Biology
#155
of 1,192 outputs
Outputs of similar age
#8,979
of 188,557 outputs
Outputs of similar age from BMC Biology
#1
of 2 outputs
Altmetric has tracked 13,583,549 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,192 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.8. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 188,557 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them